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TensorFlow.NET
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basic gradient works and switch to r2.2 native.

tags/v0.20
Oceania2018 5 years ago
parent
22d56abac8
commit
15bcc7249b
21 changed files with 272 additions and 159 deletions
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  1. +0
    -44
      TensorFlow.NET.sln
  2. +1
    -1
      src/TensorFlowNET.Core/APIs/c_api.cs
  3. +34
    -0
      src/TensorFlowNET.Core/Eager/EagerOperation.cs
  4. +3
    -0
      src/TensorFlowNET.Core/Eager/EagerTensor.Implicit.cs
  5. +7
    -27
      src/TensorFlowNET.Core/Eager/EagerTensor.cs
  6. +16
    -2
      src/TensorFlowNET.Core/Eager/c_api.eager.cs
  7. +3
    -1
      src/TensorFlowNET.Core/Eager/wrap_tfe_src.TFE_FastPathExecute.cs
  8. +4
    -4
      src/TensorFlowNET.Core/Gradients/GradientActor.cs
  9. +2
    -2
      src/TensorFlowNET.Core/Gradients/ops.gradient_function_mapping.cs
  10. +2
    -2
      src/TensorFlowNET.Core/Operations/Operation.Input.cs
  11. +8
    -2
      src/TensorFlowNET.Core/Operations/gen_array_ops.cs
  12. +74
    -44
      src/TensorFlowNET.Core/Operations/gen_math_ops.cs
  13. +37
    -16
      src/TensorFlowNET.Core/Operations/gen_resource_variable_ops.cs
  14. +1
    -11
      src/TensorFlowNET.Core/TensorFlow.Binding.csproj
  15. +2
    -0
      src/TensorFlowNET.Core/Tensors/constant_op.cs
  16. +1
    -0
      src/TensorFlowNET.Core/Tensors/dtypes.cs
  17. +6
    -0
      src/TensorFlowNET.Core/Variables/ResourceVariable.cs
  18. +42
    -0
      src/TensorFlowNET.Core/tensorflow.cs
  19. +27
    -0
      test/TensorFlowNET.UnitTest/Eager/GradientEagerTest.cs
  20. +1
    -2
      test/TensorFlowNET.UnitTest/Tensorflow.UnitTest.csproj
  21. +1
    -1
      test/Tensorflow.Keras.UnitTest/Tensorflow.Keras.UnitTest.csproj

+ 0
- 44
TensorFlow.NET.sln View File

@@ -16,95 +16,51 @@ EndProject
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Publish|Any CPU = Publish|Any CPU
Publish|x64 = Publish|x64
Release|Any CPU = Release|Any CPU
Release|x64 = Release|x64
EndGlobalSection
GlobalSection(ProjectConfigurationPlatforms) = postSolution
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EndGlobalSection
GlobalSection(SolutionProperties) = preSolution
HideSolutionNode = FALSE


+ 1
- 1
src/TensorFlowNET.Core/APIs/c_api.cs View File

@@ -43,7 +43,7 @@ namespace Tensorflow
/// </summary>
public partial class c_api
{
public const string TensorFlowLibName = "tensorflow";
public const string TensorFlowLibName = @"D:\SciSharp\tensorflow-google\bazel-bin\tensorflow\tensorflow.dll";

public static string StringPiece(IntPtr handle)
{


+ 34
- 0
src/TensorFlowNET.Core/Eager/EagerOperation.cs View File

@@ -0,0 +1,34 @@
using System;
using System.Collections.Generic;
using System.Text;

namespace Tensorflow.Eager
{
public class EagerOperation : Operation
{
public int NumInputs;
public Tensor[] Inputs { get; set; }

public EagerOperation() : base(IntPtr.Zero) { }

public override InputList inputs
{
get
{
if (_inputs_val == null)
{
var retval = new Tensor[NumInputs];

for (int i = 0; i < NumInputs; i++)
{

}

_inputs_val = new InputList(Inputs);
}

return _inputs_val;
}
}
}
}

+ 3
- 0
src/TensorFlowNET.Core/Eager/EagerTensor.Implicit.cs View File

@@ -10,5 +10,8 @@ namespace Tensorflow.Eager
{
public static explicit operator TFE_TensorHandle(EagerTensor tensor)
=> tensor.tfe_tensor_handle;

public static implicit operator IntPtr(EagerTensor tensor)
=> tensor.EagerTensorHandle;
}
}

+ 7
- 27
src/TensorFlowNET.Core/Eager/EagerTensor.cs View File

@@ -24,31 +24,10 @@ namespace Tensorflow.Eager
tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
}

public EagerTensor(int value, string device_name) : base(value)
{
tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
EagerTensorHandle = c_api.TFE_EagerTensorFromHandle(tf.context, tfe_tensor_handle);
}

public EagerTensor(float value, string device_name) : base(value)
{
tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
EagerTensorHandle = c_api.TFE_EagerTensorFromHandle(tf.context, tfe_tensor_handle);
}

public EagerTensor(float[] value, string device_name) : base(value)
{
tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
}

public EagerTensor(double[] value, string device_name) : base(value)
{
tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
}

public EagerTensor(NDArray value, string device_name) : base(value)
{
tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
EagerTensorHandle = c_api.TFE_EagerTensorFromHandle(tf.context, tfe_tensor_handle);
}

public override string ToString()
@@ -56,23 +35,24 @@ namespace Tensorflow.Eager
switch (rank)
{
case -1:
return $"tf.Tensor: shape=<unknown>, dtype={dtype.as_numpy_name()}, numpy={GetFormattedString()}";
return $"tf.Tensor: shape=<unknown>, dtype={dtype.as_numpy_name()}, numpy={GetFormattedString(dtype, numpy())}";
case 0:
return $"tf.Tensor: shape=(), dtype={dtype.as_numpy_name()}, numpy={GetFormattedString()}";
return $"tf.Tensor: shape=(), dtype={dtype.as_numpy_name()}, numpy={GetFormattedString(dtype, numpy())}";
default:
return $"tf.Tensor: shape=({string.Join(",", shape)}), dtype={dtype.as_numpy_name()}, numpy={GetFormattedString()}";
return $"tf.Tensor: shape=({string.Join(",", shape)}), dtype={dtype.as_numpy_name()}, numpy={GetFormattedString(dtype, numpy())}";
}
}

private string GetFormattedString()
public static string GetFormattedString(TF_DataType dtype, NDArray nd)
{
var nd = numpy();
switch (dtype)
{
case TF_DataType.TF_STRING:
return $"b'{(string)nd}'";
case TF_DataType.TF_BOOL:
return (nd.GetByte(0) > 0).ToString();
case TF_DataType.TF_RESOURCE:
return "<unprintable>";
default:
return nd.ToString();
}


+ 16
- 2
src/TensorFlowNET.Core/Eager/c_api.eager.cs View File

@@ -11,8 +11,18 @@ namespace Tensorflow
public static extern void TFE_RegisterGradientFunction(_gradient_function_callback callbackPointer);

[UnmanagedFunctionPointer(CallingConvention.StdCall)]
public delegate void _gradient_function_callback(string op_name, int num_inputs, IntPtr attrs, int num_attrs);
public delegate IntPtr _gradient_function_callback(string op_name, int num_inputs, IntPtr[] op_inputs, int num_attrs, IntPtr[] output_grads);

[DllImport(TensorFlowLibName)]
public static extern IntPtr VSpace_Handle(VSpace_callback_Ones ones, VSpace_callback_AggregateGrads aggregate_grads);
[UnmanagedFunctionPointer(CallingConvention.StdCall)]
public delegate IntPtr VSpace_callback_Ones(long[] shape, int dims, TF_DataType dtype);
[UnmanagedFunctionPointer(CallingConvention.StdCall)]
public delegate IntPtr VSpace_callback_AggregateGrads(IntPtr gradients, int num_grads);

[DllImport(TensorFlowLibName)]
public static extern void TFE_RegisterVSpace(IntPtr vspace);
/// <summary>
/// Return a new options object.
/// </summary>
@@ -330,7 +340,10 @@ namespace Tensorflow
string name,
IntPtr[] args,
int input_size,
TFE_FastPathExecute_SetOpAttrs set_op_attrs,
IntPtr status);
[UnmanagedFunctionPointer(CallingConvention.StdCall)]
public delegate void TFE_FastPathExecute_SetOpAttrs(IntPtr op);

[DllImport(TensorFlowLibName)]
public static extern IntPtr TFE_TapeSetNew(bool persistent, bool watch_accessed_variables);
@@ -342,7 +355,8 @@ namespace Tensorflow
public static extern void TFE_TapeWatch(IntPtr tape, IntPtr tensor);

[DllImport(TensorFlowLibName)]
public static extern IntPtr TFE_TapeGradient(IntPtr tape, IntPtr[] target, int target_size,
public static extern IntPtr TFE_TapeGradient(IntPtr tape,
IntPtr[] target, int target_size,
IntPtr[] sources, int source_size,
IntPtr status);
}


+ 3
- 1
src/TensorFlowNET.Core/Eager/wrap_tfe_src.TFE_FastPathExecute.cs View File

@@ -11,6 +11,8 @@ namespace Tensorflow.Eager
public partial class wrap_tfe_src
{
static int kFastPathExecuteInputStartIndex = 0;

[Obsolete]
public static EagerTensor TFE_FastPathExecute(Context ctx,
string device_name,
string opName,
@@ -203,7 +205,7 @@ namespace Tensorflow.Eager
/// <param name="attr_value"></param>
/// <param name="attr_list_sizes"></param>
/// <param name="status"></param>
private static void SetOpAttrWithDefaults(Context ctx, IntPtr op, AttrDef attr,
public static void SetOpAttrWithDefaults(Context ctx, IntPtr op, AttrDef attr,
string attr_name, object attr_value,
Dictionary<string, long> attr_list_sizes,
Status status)


+ 4
- 4
src/TensorFlowNET.Core/Gradients/GradientActor.cs View File

@@ -74,12 +74,12 @@ namespace Tensorflow.Gradients
}

using var status = new Status();
var et = c_api.TFE_TapeGradient(_tape,
new IntPtr[] { (target as EagerTensor).EagerTensorHandle }, 1,
new IntPtr[] { (sources as EagerTensor).EagerTensorHandle }, 1,
var et = c_api.TFE_TapeGradient(_tape,
new [] { (target as EagerTensor).EagerTensorHandle }, 1,
new [] { (sources as EagerTensor).EagerTensorHandle }, 1,
status);
status.Check(true);
return et;
return new EagerTensor(et);
}

public void Dispose()


+ 2
- 2
src/TensorFlowNET.Core/Gradients/ops.gradient_function_mapping.cs View File

@@ -24,9 +24,9 @@ namespace Tensorflow
{
public partial class ops
{
static Dictionary<string, Func<Operation, Tensor[], Tensor[]>> gradientFunctions = null;
public static Dictionary<string, Func<Operation, Tensor[], Tensor[]>> gradientFunctions = null;

private static void RegisterFromAssembly()
public static void RegisterFromAssembly()
{
if (gradientFunctions == null)
{


+ 2
- 2
src/TensorFlowNET.Core/Operations/Operation.Input.cs View File

@@ -40,9 +40,9 @@ namespace Tensorflow
public int NumInputs => c_api.TF_OperationNumInputs(_handle);
private TF_DataType[] _input_types => _inputs_val._inputs.Select(x => x.dtype).ToArray();

private InputList _inputs_val;
protected InputList _inputs_val;

public InputList inputs
public virtual InputList inputs
{
get
{


+ 8
- 2
src/TensorFlowNET.Core/Operations/gen_array_ops.cs View File

@@ -152,8 +152,14 @@ namespace Tensorflow
{
if(tf.context.executing_eagerly())
{
var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name, "Pack", name, null, values, "axis", axis);
return _result;
using var status = new Status();
var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"Pack", name,
values.Select(x => (x as EagerTensor).EagerTensorHandle).ToArray(), 1,
(op) => wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "axis", axis, null, status),
status);
status.Check(true);
return new EagerTensor(tensor);
}

var _op = _op_def_lib._apply_op_helper("Pack", name: name, args: new { values, axis });


+ 74
- 44
src/TensorFlowNET.Core/Operations/gen_math_ops.cs View File

@@ -41,6 +41,18 @@ namespace Tensorflow
/// <returns></returns>
public static Tensor add_n(Tensor[] inputs, string name = null)
{
if (tf.context.executing_eagerly())
{
using var status = new Status();
var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"AddN", name,
inputs.Select(x => (x as EagerTensor).EagerTensorHandle).ToArray(), inputs.Length,
null,
status);
status.Check(true);
return new EagerTensor(_result);
}

var _op = _op_def_lib._apply_op_helper("AddN", name, args: new { inputs });

return _op.outputs[0];
@@ -121,10 +133,18 @@ namespace Tensorflow
{
try
{
var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name,
"Mean", name, null,
input, axis, "keep_dims", keep_dims);
return _result;
using var status = new Status();
var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"Mean", name,
new IntPtr[]
{
(input as EagerTensor).EagerTensorHandle,
(axis as EagerTensor).EagerTensorHandle
}, 2,
(op) => wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "keep_dims", keep_dims, null, status),
status);
status.Check(true);
return new EagerTensor(tensor);
}
catch (Exception)
{
@@ -196,17 +216,15 @@ namespace Tensorflow
{
if (tf.context.executing_eagerly())
{
using (var status = new Status())
{
var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"Add", name, new IntPtr[]
{
(x as EagerTensor).EagerTensorHandle,
(y as EagerTensor).EagerTensorHandle
}, 2, status);
status.Check(true);
return new EagerTensor(_result);
}
using var status = new Status();
var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"Add", name, new IntPtr[]
{
(x as EagerTensor).EagerTensorHandle,
(y as EagerTensor).EagerTensorHandle
}, 2, null, status);
status.Check(true);
return new EagerTensor(_result);
}

var _op = _op_def_lib._apply_op_helper("Add", name, args: new { x, y });
@@ -574,10 +592,18 @@ namespace Tensorflow
{
if (tf.context.executing_eagerly())
{
var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name,
"Cast", name, null,
x, "DstT", DstT, "Truncate", Truncate);
return _result;
using var status = new Status();
var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"Cast", name,
new IntPtr[] { (x as EagerTensor).EagerTensorHandle }, 1,
(op) =>
{
wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "DstT", DstT, null, status);
wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "Truncate", Truncate, null, status);
},
status);
status.Check(true);
return new EagerTensor(tensor);
}

var _op = _op_def_lib._apply_op_helper("Cast", name, args: new { x, DstT, Truncate });
@@ -619,17 +645,15 @@ namespace Tensorflow
{
if (tf.context.executing_eagerly())
{
using (var status = new Status())
{
var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"Sub", name, new IntPtr[]
{
(x as EagerTensor).EagerTensorHandle,
(y as EagerTensor).EagerTensorHandle
}, 2, status);
status.Check(true);
return new EagerTensor(_result);
}
using var status = new Status();
var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"Sub", name, new IntPtr[]
{
(x as EagerTensor).EagerTensorHandle,
(y as EagerTensor).EagerTensorHandle
}, 2, null, status);
status.Check(true);
return new EagerTensor(_result);
}

var _op = _op_def_lib._apply_op_helper("Sub", name, args: new { x, y });
@@ -717,11 +741,11 @@ namespace Tensorflow
{
using var status = new Status();
var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"Mul", name, new IntPtr[]
{
(x as EagerTensor).EagerTensorHandle,
(y as EagerTensor).EagerTensorHandle
}, 2, status);
"Mul", name, new IntPtr[]
{
(x as EagerTensor).EagerTensorHandle,
(y as EagerTensor).EagerTensorHandle
}, 2, null, status);
status.Check(true);
return new EagerTensor(_result);
}
@@ -757,17 +781,15 @@ namespace Tensorflow
{
if (tf.context.executing_eagerly())
{
using (var status = new Status())
{
var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
using var status = new Status();
var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"RealDiv", name, new IntPtr[]
{
(x as EagerTensor).EagerTensorHandle,
(y as EagerTensor).EagerTensorHandle
}, 2, status);
status.Check(true);
return new EagerTensor(_result);
}
}, 2, null, status);
status.Check(true);
return new EagerTensor(_result);
}

var _op = _op_def_lib._apply_op_helper("RealDiv", name, args: new { x, y });
@@ -962,8 +984,16 @@ namespace Tensorflow
{
if (tf.context.executing_eagerly())
{
var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name, "Range", name, null, start, limit, delta);
return _result;
using var status = new Status();
var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"Range", name, new IntPtr[]
{
(start as EagerTensor).EagerTensorHandle,
(limit as EagerTensor).EagerTensorHandle,
(delta as EagerTensor).EagerTensorHandle
}, 3, null, status);
status.Check(true);
return new EagerTensor(tensor);
}

var _op = _op_def_lib._apply_op_helper("Range", name, new { start, limit, delta });


+ 37
- 16
src/TensorFlowNET.Core/Operations/gen_resource_variable_ops.cs View File

@@ -14,6 +14,8 @@
limitations under the License.
******************************************************************************/

using System;
using System.Linq;
using Tensorflow.Eager;
using static Tensorflow.Binding;

@@ -27,10 +29,16 @@ namespace Tensorflow
{
if (tf.context.executing_eagerly())
{
var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name,
"AssignVariableOp", name, null,
resource, value);
return _result;
using var status = new Status();
var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"AssignVariableOp", name,
new[]
{
(resource as EagerTensor).EagerTensorHandle,
(value as EagerTensor).EagerTensorHandle
}, 2, null, status);
status.Check(true);
return tensor;
}

var _op = _op_def_lib._apply_op_helper("AssignVariableOp", name, new { resource, value });
@@ -42,10 +50,13 @@ namespace Tensorflow
{
if (tf.context.executing_eagerly())
{
var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name,
"VarIsInitializedOp", name, null,
resource);
return _result;
using var status = new Status();
var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"VarIsInitializedOp", name,
new[] { (resource as EagerTensor).EagerTensorHandle },
1, null, status);
status.Check(true);
return new EagerTensor(tensor);
}

var _op = _op_def_lib._apply_op_helper("VarIsInitializedOp", name, new { resource });
@@ -67,10 +78,17 @@ namespace Tensorflow
{
if (tf.context.executing_eagerly())
{
var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name,
"VarHandleOp", name, null,
"container", container, "shared_name", shared_name, "dtype", dtype, "shape", shape.dims);
return _result;
using var status = new Status();
var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"VarHandleOp", name, null, 0, op =>
{
wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "container", container, null, status);
wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "shared_name", shared_name, null, status);
wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "dtype", dtype, null, status);
wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "shape", shape.dims, null, status);
}, status);
status.Check(true);
return new EagerTensor(tensor);
}

var _op = _op_def_lib._apply_op_helper("VarHandleOp", name, new {
@@ -94,10 +112,13 @@ namespace Tensorflow
{
if (tf.context.executing_eagerly())
{
var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name,
"ReadVariableOp", name, null,
resource, "dtype", dtype);
return _result;
using var status = new Status();
var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
"ReadVariableOp", name, new IntPtr[] { (resource as EagerTensor).EagerTensorHandle }, 1,
(op) => wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "dtype", dtype, null, status),
status);
status.Check(true);
return new EagerTensor(tensor);
}

var _op = _op_def_lib._apply_op_helper("ReadVariableOp", name, new


+ 1
- 11
src/TensorFlowNET.Core/TensorFlow.Binding.csproj View File

@@ -31,7 +31,7 @@ https://tensorflownet.readthedocs.io</Description>
<PackageRequireLicenseAcceptance>true</PackageRequireLicenseAcceptance>
<SignAssembly>true</SignAssembly>
<AssemblyOriginatorKeyFile>Open.snk</AssemblyOriginatorKeyFile>
<Platforms>AnyCPU;x64</Platforms>
<Platforms>AnyCPU</Platforms>
</PropertyGroup>

<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|AnyCPU'">
@@ -40,20 +40,10 @@ https://tensorflownet.readthedocs.io</Description>
<PlatformTarget>x64</PlatformTarget>
</PropertyGroup>

<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
<AllowUnsafeBlocks>true</AllowUnsafeBlocks>
<DefineConstants>TRACE;DEBUG;SERIALIZABLE_</DefineConstants>
<PlatformTarget>x64</PlatformTarget>
</PropertyGroup>

<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|AnyCPU'">
<AllowUnsafeBlocks>true</AllowUnsafeBlocks>
</PropertyGroup>

<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
<AllowUnsafeBlocks>true</AllowUnsafeBlocks>
</PropertyGroup>

<ItemGroup>
<Compile Remove="Distribute\**" />
<Compile Remove="Models\**" />


+ 2
- 0
src/TensorFlowNET.Core/Tensors/constant_op.cs View File

@@ -127,6 +127,8 @@ namespace Tensorflow
return new EagerTensor(val, ctx.device_name);
case float val:
return new EagerTensor(val, ctx.device_name);
case float[,] val:
return new EagerTensor(val, ctx.device_name);
case double val:
return new EagerTensor(val, ctx.device_name);
case float[] val:


+ 1
- 0
src/TensorFlowNET.Core/Tensors/dtypes.cs View File

@@ -202,6 +202,7 @@ namespace Tensorflow
TF_DataType.TF_INT32 => "int32",
TF_DataType.TF_FLOAT => "float32",
TF_DataType.TF_BOOL => "bool",
TF_DataType.TF_RESOURCE => "resource",
_ => type.ToString()
};



+ 6
- 0
src/TensorFlowNET.Core/Variables/ResourceVariable.cs View File

@@ -18,6 +18,7 @@ using Google.Protobuf;
using NumSharp;
using System;
using System.Collections.Generic;
using Tensorflow.Eager;
using static Tensorflow.Binding;

namespace Tensorflow
@@ -221,5 +222,10 @@ namespace Tensorflow
return array_ops.identity(value);
});
}

public override string ToString()
{
return $"tf.Variable: '{name}' shape={string.Join(",", shape)}, dtype={dtype.as_numpy_name()}, numpy={EagerTensor.GetFormattedString(dtype, numpy())}";
}
}
}

+ 42
- 0
src/TensorFlowNET.Core/tensorflow.cs View File

@@ -14,6 +14,9 @@
limitations under the License.
******************************************************************************/

using System;
using System.Linq;
using System.Runtime.InteropServices;
using System.Threading;
using Tensorflow.Eager;

@@ -39,6 +42,45 @@ namespace Tensorflow
public tensorflow()
{
_constructThreadingObjects();
InitGradientEnvironment();
}

private unsafe void InitGradientEnvironment()
{
var vspace = c_api.VSpace_Handle((shape, dims, dtype) =>
{
var ones = constant_op.constant(1.0f, dtype: dtype) as EagerTensor;
return ones.EagerTensorHandle;
}, (gradients, num_grads) =>
{
var input_grads = new EagerTensor[num_grads];
for (int i = 0; i < num_grads; i++)
input_grads[i] = new EagerTensor(*((IntPtr*)gradients + i));

var add_n = gen_math_ops.add_n(input_grads);
return (add_n as EagerTensor).EagerTensorHandle;
});

ops.RegisterFromAssembly();
c_api.TFE_RegisterGradientFunction((op_name, num_inputs, op_inputs, num_attrs, output_grads) =>
{
var output_grad_tensors = output_grads.Select(x => new EagerTensor(x)).ToArray();

var input_tensors = new EagerTensor[num_inputs];
for (int i = 0; i < num_inputs; i++)
input_tensors[i] = new EagerTensor(op_inputs[op_inputs.Length == 1 ? 0 : i]);

var gradients = ops.gradientFunctions[op_name](new EagerOperation
{
NumInputs = num_inputs,
Inputs = input_tensors
}, output_grad_tensors);

var ret_tensors = Marshal.AllocHGlobal(sizeof(IntPtr) * num_inputs);
Marshal.Copy(gradients.Select(x => (x as EagerTensor).EagerTensorHandle).ToArray(), 0, ret_tensors, 2);
// Marshal.FreeHGlobal(ret_tensors);
return ret_tensors;
});
}

public ResourceVariable Variable<T>(T data,


+ 27
- 0
test/TensorFlowNET.UnitTest/Eager/GradientEagerTest.cs View File

@@ -0,0 +1,27 @@
using System;
using System.Collections.Generic;
using System.Linq;
using Microsoft.VisualStudio.TestTools.UnitTesting;
using Tensorflow;
using static Tensorflow.Binding;

namespace TensorFlowNET.UnitTest.Gradient
{
[TestClass]
public class GradientEagerTest : PythonTest
{
[TestMethod]
public void ConstantSq()
{
// Calcute the gradient of w * w
// by Automatic Differentiation in Eager mode
// in tensorflow.net 2.x that is in development intensively
var w = tf.constant(1.5f);
using var tape = tf.GradientTape();
tape.watch(w);
var loss = w * w;
var grad = tape.gradient(loss, w);
print(grad);
}
}
}

+ 1
- 2
test/TensorFlowNET.UnitTest/Tensorflow.UnitTest.csproj View File

@@ -30,11 +30,10 @@

<ItemGroup>
<PackageReference Include="FluentAssertions" Version="5.10.3" />
<PackageReference Include="Microsoft.NET.Test.Sdk" Version="16.5.0" />
<PackageReference Include="Microsoft.NET.Test.Sdk" Version="16.6.1" />
<PackageReference Include="MSTest.TestAdapter" Version="2.1.1" />
<PackageReference Include="MSTest.TestFramework" Version="2.1.1" />
<PackageReference Include="NumSharp.Lite" Version="0.1.7" />
<PackageReference Include="SciSharp.TensorFlow.Redist" Version="2.1.0" />
</ItemGroup>

<ItemGroup>


+ 1
- 1
test/Tensorflow.Keras.UnitTest/Tensorflow.Keras.UnitTest.csproj View File

@@ -7,7 +7,7 @@
</PropertyGroup>

<ItemGroup>
<PackageReference Include="Microsoft.NET.Test.Sdk" Version="16.5.0" />
<PackageReference Include="Microsoft.NET.Test.Sdk" Version="16.6.1" />
<PackageReference Include="MSTest.TestAdapter" Version="2.1.1" />
<PackageReference Include="MSTest.TestFramework" Version="2.1.1" />
<PackageReference Include="coverlet.collector" Version="1.2.1">


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